A Bayesian K-PD model for synergy: A case study
| Autor: | Christel Faes, Fabiola La Gamba, Helena Geys, Tom Jacobs, Luc Ver Donck |
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| Rok vydání: | 2018 |
| Předmět: |
Pharmacology
Statistics and Probability Change over time Dose-Response Relationship Drug Computer science Bayesian probability Bayes Theorem Drug Synergism Model parameters Dose level Bayesian inference Models Biological 030226 pharmacology & pharmacy 01 natural sciences 010104 statistics & probability 03 medical and health sciences 0302 clinical medicine Frequentist inference Pharmacodynamics Humans Drug Therapy Combination Pharmacology (medical) 0101 mathematics Biological system Indirect response |
| Zdroj: | Pharmaceutical Statistics |
| ISSN: | 1539-1604 |
| DOI: | 10.1002/pst.1887 |
| Popis: | Coadministration of 2 or more compounds can alter both the pharmacokinetics and pharmacodynamics of individual compounds. While experiments on pharmacodynamic drug-drug interactions are usually performed in an in vitro setting, this experiment focuses on an in vivo setting. The change over time of a safety biomarker is modeled using an indirect response model, in which the virtual pharmacokinetic profile of one compound drives the effect of the other. Several experiments at different dose level combinations were performed sequentially. While a traditional frequentist analysis consists of estimating the model parameters based on all the data simultaneously, in this work, we consider a Bayesian inference framework allowing to incorporate the results from a historical dose-response experiment. |
| Databáze: | OpenAIRE |
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